Triple
T19335435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brownhelm Township |
E483609
|
entity |
| Predicate | hasLegislativeBodySize |
P63806
|
FINISHED |
| Object | three-member board of trustees |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: three-member board of trustees | Statement: [Brownhelm Township, hasLegislativeBodySize, three-member board of trustees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegislativeBodySize Context triple: [Brownhelm Township, hasLegislativeBodySize, three-member board of trustees]
-
A.
governingBodySize
chosen
Indicates the number of members or the overall size of the group that serves as the governing body for an entity.
-
B.
totalNumberOfLegislators
Indicates the total count of legislators associated with a given political body, jurisdiction, or legislative session.
-
C.
numberOfLegislatures
Indicates the total count of distinct legislatures associated with or relevant to a given entity.
-
D.
legislativeBodyOf
Indicates that one entity is the official legislative body (lawmaking assembly) of another entity, typically a political unit such as a country, state, or city.
-
E.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61644b80c819080f9bca086424a36 |
completed | April 20, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.